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A new design of delay-dependent robust H_∞ filtering for continuous-time polytopic systems with time-varying delay

INTERNATIONAL JOURNAL OF ROBUST AND NONlinear CONTROL 2010年第3期20卷 346-365页

作者： Qiu, Jianbin Feng, Gang Yang, Jie USTC & City Univ Hong Kong Joint Adv Res Ctr Dept Mfg Engn & Engn Management Suzhou 215123 Peoples R China City Univ Hong Kong Dept Mfg Engn & Engn Management Hong Kong Hong Kong Peoples R China Univ Sci & Technol China Dept Precis Machinery & Precis Instrumentat Hefei 230026 Peoples R China

This paper revisits the problem of delay-dependent robust H-infinity filtering design for a class of continuous-time polytopic linear systems with a time-varying state delay. Based on a newly developed parameter-dependent Lyapunov-Krasovskii functional combined with Projection Lemma and an improved free-weighting matrix technique for delay-dependent criteria, a new sufficient condition for robust H-infinity performance analysis is first derived and then the filter synthesis is developed by using a simple matrix inequality linearization technique. It is shown that the desired filters can be constructed by solving a set of linear matrix inequalities. Finally, two simulation examples are given to show the effectiveness and less conservatism of the proposed method in comparison with the existing approaches. Copyright (C) 2009 John Wiley & Sons, Ltd.

关键词： continuous-time linear systems time-varying delay delay and parameter-dependent H-infinity filtering linear matrix inequalities

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Adaptive output-feedback quadratic tracking control of continuous-time systems via value iteration with its application

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IET CONTROL THEORY AND APPLICATIONS 2020年第20期14卷 3621-3631页

作者： Peng, Yunjian Meng, Qingqing Sun, Weijie South China Univ Technol Sch Automat Sci & Engn Guangzhou 510641 Guangdong Peoples R China

This study is dedicated to develop an adaptive output-feedback (OPFB) tracking control scheme for continuous-time linear systems to achieve the infinite-horizon linear quadratic tracking (LQT) solution. The existence conditions of the OPFB control for LQT solution are proposed and an upper bound is found for the discount factor to assure the stability of the OPFB solution. To develop an online learning solution without knowing the system drift dynamics, a novel value iteration (VI) algorithm is presented based on the integral reinforcement learning technique which requires measured augmented system states. Moreover, a convergence analysis is proposed for the VI algorithm. Compared to the policy iteration method, the VI algorithm relaxes the initial stabilising control policy requirement. Specifically, in order to further obviate the knowledge of system states, a neural network-based adaptive observer is used during learning and it is no longer needed after the online learning algorithm converges. Effectiveness of the proposed learning scheme is illustrated through an interesting application into a single-phase grid-connected PV power inverter.

关键词： optimal control adaptive control iterative methods linear quadratic control discrete time systems learning (artificial intelligence) feedback linear systems dynamic programming continuous time systems neurocontrollers nonlinear control systems photovoltaic power systems control system synthesis closed loop systems stability observers continuous-time linear systems infinite-horizon linear quadratic tracking solution existence conditions OPFB control LQT solution OPFB solution online learning solution system drift dynamics integral reinforcement learning technique augmented system states VI algorithm policy iteration method initial stabilising control policy requirement neural network-based adaptive observer learning scheme adaptive output-feedback quadratic tracking control continuous-time systems value iteration adaptive output-feedback tracking control scheme

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Orthogonal Polynomial Bases for Data-Driven Analysis and Control of continuous-time systems

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2024年第7期69卷 4307-4319页

作者： Rapisarda, P. van Waarde, Henk J. Camlibel, M. K. Univ Southampton Sch Elect & Comp Sci Southampton SO17 1BJ Hants England Univ Groningen Bernoulli Inst Math Comp Sci & Artificial Intelli NL-9747 AG Groningen Netherlands

We use polynomial approximation theory to perform data-driven analysis and control of linear, continuous-time invariant systems. We transform the continuous-time input trajectories and state trajectories into discrete sequences consisting of the coefficients of their orthogonal polynomial bases representations. We show that the dynamics of the transformed input signals and state signals and those of the original continuous-time trajectories are described by the same system matrices. We investigate informativity, quadratic stabilization, and H-2-performance problems for continuous-time systems. We deal with the case in which machine-precision accuracy in the representation of continuous-time signals can be achieved from the data using a finite number of basis elements, and the case in which the approximation error is nonnegligible.

关键词： Trajectory Approximation error Chebyshev approximation System dynamics Standards Transforms Controllability H-2-performance continuous-time linear systems data-driven control informativity polynomial orthogonal basis quadratic stabilization

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Model predictive control of switching continuous-time systems with stochastic jumps: Application to an electric current source

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IET CONTROL THEORY AND APPLICATIONS 2022年第4期16卷 454-463页

作者： Vargas, Alessandro N. Ishihara, Joao Y. Caruntu, Constantin F. Zhang, Lixian Nanha Djanan, Armand A. Univ Tecnol Fed Parana Procopio PR Brazil Univ Brasilia FT UnB Brasilia DF Brazil Gheorghe Asachi Tech Univ Iasi Dept Automat Control & Appl Informat Iasi Romania Harbin Inst Technol Res Inst Intelligent Control & Syst Harbin Peoples R China Univ Yaounde I Fac Sci Lab Modelling & Simulat Engn Biomimet & Prototype POB 812 Yaounde Cameroon

This paper proposes an extension of the model predictive control framework for switching continuous-time linear systems. The switching times follow a stochastic process with limited statistical information. At each switching time, the controller knows the system state, but it is blind with respect to the switching continuous-time subsystems. In this setting, the paper's main contribution is to show how to compute the model predictive control gain. The paper also illustrates the implications of our approach for applications. The approach was used in practice to control an electric current source that supplied a switching load. The experimental data support the usefulness of our approach.

关键词： electric current source stochastic process statistical analysis linear systems stochastic processes statistical information switching continuous-time subsystems continuous time systems electric current control predictive control model predictive control framework continuous-time linear systems

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Supervisory Nonlinear State Observers for Adversarial Sparse Attacks

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IEEE TRANSACTIONS ON CYBERNETICS 2022年第3期52卷 1575-1587页

作者： An, Liwei Yang, Guang-Hong Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Peoples R China Northeastern Univ State Key Lab Synthet Automat Proc Ind Shenyang 110819 Peoples R China

This article investigates the problem of secure state estimation for continuous-time linear systems in the presence of sparse sensor attacks. Compared with the existing results, the attacked sensor set can be changed by adversaries against secure estimation. To address the more erratic attacks, a novel supervisory state observer is proposed, which employs a bank of candidate nonlinear subobservers and a switching logic administrated by a monitoring function to select the active subobserver at every instant of time. Based on the stability analysis of switched systems, it is proven that the supervisory observer asymptotically converges to a neighborhood of the true system state in the presence of the sensor attacks and bounded disturbances. A simulation example is given to substantiate the theoretical results.

关键词： Observers Switches linear systems Symmetric matrices Monitoring continuous-time linear systems linear matrix inequalities (LMIs) location-varying sparse (LVS) attacks supervisory nonlinear observers

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A Novel Parallel Control Method for continuous-time linear Output Regulation With Disturbances

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IEEE TRANSACTIONS ON CYBERNETICS 2023年第6期53卷 3760-3770页

作者： Wei, Qinglai Li, Hongyang Wang, Fei-Yue Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Macau Univ Sci & Technol Inst Syst Engn Taipa Macao Peoples R China Qingdao Acad Intelligent Ind Qingdao 266109 Peoples R China

In this article, a novel linear parallel control method is developed for output regulation problems with disturbances. The traditional feedback regulators are passive regulation methods. In order to solve this problem, the parallel controllers are presented, where the time variation of the control is constructed instead of the control value itself, to stabilize the output of the system. The main contributions of the developed method include two aspects: 1) a novel parallel regulator structure is presented, which can provide greater flexibility comparing with traditional methods and 2) the necessary and sufficient conditions for the existence of parallel regulators are analyzed. First, the structure of the linear parallel regulators is provided. Next, considering the situations that the full system information is obtained and the information of error is obtained, respectively, the properties of the parallel regulators are analyzed, and the regulator designs for the two situations are provided. Finally, numerical examples are provided to verify the correctness of the present method.

关键词： Regulators Regulation Control systems Stability analysis Asymptotic stability Eigenvalues and eigenfunctions Control theory continuous-time linear systems output regulation parallel control theory parallel regulators parallel systems

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On applications of the ray-shooting method for structured and structured-sparse static-output-feedbacks

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INTERNATIONAL JOURNAL OF systems SCIENCE 2017年第9期48卷 1902-1913页

作者： Peretz, Y. Jerusalem Coll Technol Comp Sci Dept Lev Acad Ctr Jerusalem Israel

A randomised optimisation method, called the ray-shooting method that efficiently solves the minimisation problem of continuous functions over compact non-convex unconnected regions, was introduced recently. Based on the ray-shooting method, an algorithm is suggested for solving the problems of structured and structured-sparse stabilising static-output-feedbacks. The algorithm presented here is a randomised algorithm, with a proof of convergence in probability. Its practical implementation has a good performance, in terms of quality of controllers, percent of success and run-time.

关键词： continuous-time linear systems state-space representation static-output-feedbacks structured controllers sparse controllers randomised algorithms approximation algorithms convergence in probability

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On a new generalised LMI condition and randomised algorithm for robust stabilisation via static-output-feedback

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INTERNATIONAL JOURNAL OF systems SCIENCE 2020年第1期51卷 61-71页

作者： Peretz, Y. Merzbach, O. Moyall, S. Jerusalem Coll Technol Lev Acad Ctr Comp Sci Dept POB 16031 Jerusalem Israel

For a given system with time-invariant affine uncertainties, ranging in a unit hypercube or, equivalently, in a hyper-rectangle, new LMI sufficient conditions for the verification of a given simultaneous static-output-feedback for hypercube nodes, being robust static-output-feedback for the whole system, are proved. The conditions generalise previous results in the sense that we do not assume that the state-to-measurement or the input-to-state matrix is constant. Based on the LMI conditions, a randomised algorithm is suggested. The effectiveness of the method is reinforced through experiments on real-life systems.

关键词： continuous-time linear systems State-space representation Feedback stability Robust stabilisabiliy Simultaneous stabilisation Static-output-feedbacks NP-hard control problems Randomised algorithms

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On Computing Solutions to the continuous time Constrained linear Quadratic Regulator

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2010年第9期55卷 2192-2198页

作者： Pannocchia, Gabriele Rawlings, James B. Mayne, David Q. Marquardt, Wolfgang Univ Pisa Dept Chem Engn I-56126 Pisa Italy Univ Wisconsin Dept Chem & Biol Engn Madison WI 53706 USA Univ London Imperial Coll Sci Technol & Med Dept Elect & Elect Engn London SW7 2AZ England Rhein Westfal TH Aachen AVT Proc Syst Engn D-52062 Aachen Germany

We propose in this note a method for computing the solution to the infinite horizon continuous-time constrained linear quadratic regulator. The method is based on two main ingredients: a multigrid method for placing a finite number of time intervals, and a piece-wise linear parameterization of the input within the intervals. The input values at the decision-time points and slopes within the time intervals are computed via quadratic programs (QPs). The grids are gradually refined to efficiently improve the accuracy of the solution, and the required matrices and vectors for all QPs are computed offline and stored to improve the online efficiency. Two examples are presented to show the main characteristics of the proposed method.

关键词： Constrained linear quadratic regulator (CLQR) continuous-time linear systems model predictive control (MPC) quadratic programs (QPs)

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On policy iteration-based discounted optimal control

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INTERNATIONAL JOURNAL OF ROBUST AND NONlinear CONTROL 2024年第7期34卷 4926-4942页

作者： Dong, Botao Huang, Longyang Ma, Xiwen Zhang, Weidong Shanghai Jiao Tong Univ Dept Automat Shanghai Peoples R China Hainan Univ Sch Informat & Commun Engn Haikou Hainan Peoples R China

This article investigates the policy iteration (PI) method for the discounted optimal control (DOC) problem of continuous-time linear systems. We show the properties and convergence of the PI method. The theory analysis shows that the convergence of PI can be ensured without requiring the initial admissible control gain. The convergence rate of the PI method is provided. An iteration-termination criterion is established for detecting the stability of the closed-loop system under the control gain obtained by executing PI. Two kinds of data-driven implementations are constructed without using prior information of the system dynamics. A simulation example is presented to validated the properties of the PI method.

关键词： continuous-time linear systems data-driven control discounted optimal control policy iteration

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